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ML Engineer — recommendations
Netflix
Este anuncio está pensado para talento nativo en IA : habilidades y herramientas claras para saber si encajas antes de aplicar — y para reducir descartes por desajuste.
3 habilidades 1 herramienta
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Modalidad Hybrid
Ubicación 5808 W Sunset Blvd, Los Angeles, CA 90028, United States · Hybrid
Compensación $190k–$260k + equity Nivel de experiencia Beneficios Top-of-market pay, freedom & responsibility culture. Cómo aplicar Sequential or embedding model at scale.
Publicada 11 jun 2026
Actualizada 11 jul 2026 Netflix is hiring a Senior ML Engineer — recommendations on the Personalization team (Hybrid · Los Angeles, United States). This is a hands-on role in LLM & generative AI —not a generic “AI enthusiast” post.
You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.
Netflix personalises what you watch next using large-scale ML and A/B culture. Los Gatos teams own recommendation and content understanding.
ML Engineer — recommendations: sequential models, embeddings, and offline/online metric alignment at global scale.
What you will do
Ship production recommendation systems with clear evaluation, monitoring, and rollback paths—not demo-only notebooks. Partner with product, design, and domain experts on requirements, trade-offs, and safe rollout. Improve data quality, labeling, and offline metrics that correlate with business KPIs. Document architectures and runbooks for on-call and customer-facing teams. Mentor engineers on testing, observability, and responsible AI practices. What we look for
Strong Python and modern ML/LLM stack experience with multiple shipped features. Comfort with SQL, experimentation, and communicating results to non-technical stakeholders. Pragmatic ownership from prototype to production—including cost and latency budgets. Eligible to work in the listed country; professional English (French a plus for Paris roles). Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
SQL
Analytical SQL for features, cohorts, label quality, and experiment analysis at scale.
✓ You can show evidence in your application: Sequential or embedding model at scale. ✓ Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, and Spark. ✓ You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals. ✓ You are comfortable with the hybrid rhythm (Hybrid · Los Angeles, United States)—onsite collaboration when it matters, deep work when remote. ✓ You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords. ✓ You read the full listing (comp: $190k–$260k + equity, benefits in At a glance) and your expectations align. Lo que pide la empresa
Sequential or embedding model at scale.
Inicia sesión con cuenta candidato para aplicar
Regístrate, añade titular y bio; luego podrás adjuntar enlace o PDF de CV en Mi cuenta antes de aplicar. Así las candidaturas quedan ligadas a tu perfil.
Sugerencias
Talento IA que podría interesarte Perfiles ordenados por solape con habilidades y herramientas de este rol — útil si contratas equipo o comparas candidatos.
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Título
ML Engineer — recommendations
Aplicar Pensado para equipos que contratan personas que trabajan con IA, no solo alrededor.
Los candidatos ven habilidades y herramientas al inicio; recibes candidaturas estructuradas en un solo panel.
Llega a profesionales de IA que buscan roles con expectativas basadas en pruebas.
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